Multivariate geostatistical simulation by minimising spatial cross-correlation

Suhrabian B., TERCAN A. E.

COMPTES RENDUS GEOSCIENCE, vol.346, pp.64-74, 2014 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 346
  • Publication Date: 2014
  • Doi Number: 10.1016/j.crte.2014.01.002
  • Journal Name: COMPTES RENDUS GEOSCIENCE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.64-74
  • Hacettepe University Affiliated: Yes

Abstract

Joint simulation of attributes in multivariate geostatistics can be achieved by transforming spatially correlated variables into independent factors. In this study, a new approach for this transformation, Minimum Spatial Cross-correlation (MSC) method, is suggested. The method is based on minimising the sum of squares of cross-variograms at different distances. In the approach, the problem in higher space (N x N) is reduced to N x (N - 1)/2 problems in the two-dimensional space and the reduced problem is solved iteratively using Gradient Descent Algorithm. The method is applied to the joint simulation of a set of multivariate data in a marble quarry and the results are compared with Minimum/Maximum Autocorrelation Factors (MAF) method. (C) 2014 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.